The gamtools process_nps tool is used to map raw sequencing data from a collection of NPs and call positive windows from those NPs to generate a segregation table. It can optionally also calculate various QC metrics for each NP, generate bigwig/bed files for visualising the raw data and calculate proximity matrices.

Usage and option summary


gamtools process_nps [OPTIONS] -g <GENOME_FILE> <FASTQ_FILE> [<FASTQ_FILE> ...]

Optional parameters:

Option Description
-o, –output_dir Write segregation, matrix etc. to this directory
-q, –minimum-mapq Filter out any mapped read with a mapping quality less than x (default is 20, use -q 0 for no filtering)
-c, –do-qc Perform sample quality control.
-i, –bigwigs Make bigWig files.
-b, –bigbeds Make bed files of positive windows
-w, –window-sizes One or more window sizes for calling positive windows
-s, –matrix-sizes Resolutions for which proximity matrices should be produced.
–qc-window-size Use this window size for qc (default is median window size).
-f, –fittings_dir Write segregation curve fitting plots to this directory
-d, –details-file If specified, write a table of fitting parameters to this path
–additional-qc-files Any additional qc files to filter on

Parameters inherited from doit:

gamtools process_nps uses doit as a task dependency engine, to determine what actions need to be performed and in which order. A number of additional command line parameters are available that control doit’s behaviour.

Option Description
–doit-db-file Doit saves information about each run in a database file. This parameter specifies the location of that database file.
–doit-backend Doit database format. (one of sqlite3, json, dbm. default: dbm)
–doit-verbosity 0 capture (do not print) stdout/stderr from task. 1 capture stdout only. 2 do not capture anything (print everything immediately). Default: 1
–doit-reporter Where should doit report the output from each task. One of (json, console, zero, executed-only). Default: console
–doit-process Number of subprocesses (default is 0, i.e. serial processing)
–doit-parallel-type Tasks can be executed in parallel in different ways: process: uses python multiprocessing module thread: uses threads. Default is process.